We use the popular XFoil simulator [1]} to compute the pressure distribution \(\textbf {y}_{i}\)  over the surface of each \(\textbf {x}_{i}\) . Even though GCNNs models are primarily designed to handle 3D shapes, they can also handle 2D ones by considering the 2D equivalent of a surface mesh, which is a discretized 2D contour. As in [2]}, train one to predict pressure values \(\tilde{\textbf {y}_{i}}\)  at each vertex along with the overall lift-to-drag ratio, which we take to be \(R(\textbf {y}_{i})\) , which could also be obtained by integrating the pressure values over the surface of the shape.
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